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Informed Bond Trading, Corporate Yield Spreads, and Corporate Default Prediction

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  • Song Han

    (Short-Term Funding Markets Section, Division of Research and Statistics, Federal Reserve Board, Washington, DC 20551)

  • Xing Zhou

    (Department of Finance and Economics, Rutgers Business School, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854)

Abstract

Taking advantage of recently augmented corporate bond transaction data, we examine the pricing implications of informed trading in corporate bonds and its ability to predict corporate defaults. We find that microstructure measures of information asymmetry seem to capture adverse selection in corporate bond trading reasonably well. We demonstrate that information asymmetry in bond trading has explanatory power for corporate bond yield spreads, and this result holds after controlling for the transaction costs of liquidity, credit risk, and other traditional bond pricing factors. Furthermore, information asymmetry can help forecast corporate defaults after conditioning on other default prediction variables. Such forecasting ability of informed bond trading is especially useful for private firms because the bond market constitutes the only venue for informed traders to exploit their information advantages. This paper was accepted by Wei Xiong, finance.

Suggested Citation

  • Song Han & Xing Zhou, 2014. "Informed Bond Trading, Corporate Yield Spreads, and Corporate Default Prediction," Management Science, INFORMS, vol. 60(3), pages 675-694, March.
  • Handle: RePEc:inm:ormnsc:v:60:y:2014:i:3:p:675-694
    DOI: 10.1287/mnsc.2013.1768
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    5. Lovreta, Lidija & Silaghi, Florina, 2020. "The surface of implied firm’s asset volatility," Journal of Banking & Finance, Elsevier, vol. 112(C).

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